VisLunch/Spring2010

This semester Guoning Chen and Josh Levine will be responsible
for organizing the VisLunch sessions. Please feel free to contact them
for any question regarding VisLunch or for scheduling a talk:

Information regarding the VisLunch sessions will posted on this wiki page (http://www.vistrails.org/index.php/VisLunch/Spring2010)

Open Discussion and Semester Planning

VisLunch is back for this semester and will be organized by Guoning Chen and Josh Levine. If you are unaware, VisLunch provides everyone at SCI a platform to present their research work and/or the latest developments in the community that could benefit the rest of us. In addition, the meeting is a great forum to give practice talks and improve your presentation skills. Plus there's _free_ pizza, and it's a nice opportunity to meet new people. Please let either Josh or Guoning know if

1.) You've submitted work to a research venue (e.g. recent conferences like Siggraph) and would like to share your ideas;

2.) You are preparing a submission to an upcoming venue (e.g. IEEE Vis, Siggraph Asia, etc.) and would like to get some feedback;

3.) Your work has been accepted to some venue and you are preparing a presentation you would like to practice; or

4.) You've recently read a new publication and are fascinated by the ideas and wish to share them with the rest of us.

Please consider volunteering to give a presentation at some point! We're hoping that there will be enough presenters so that we don't cancel any future weeks.

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May 14, 2010

Rob Ross

May 7, 2010

Finals Week

Apr. 30, 2010

Finals Week

Apr. 2, 2010

Ramon

Mar. 26, 2010

Spring Break

Mar. 19, 2010

Tiago Etiene

Mar. 12, 2010

- Data-Intensive Scientific Visualization in the Cloud: Challenges and Opportunities

Large-scale scientific visualization systems are historically designed for "throwing datasets" - pushing pre-conditioned data as quickly as possible through the graphics pipeline. However, increasingly, scalable data manipulation, restructuring, and querying -- tasks at which the data management community has provided excellent tools -- are considered integral parts of exploratory visualization. We observe that the visualization community tends to support these tasks only through ad hoc extensions to existing visualization systems. We advocate a different approach: implement and evaluate a core set of visualization algorithms in a high-level, share-nothing parallel dataflow system. Analysis of such algorithms can be used to inform requirements for a system that bridges the gap between scalable visualization and scalable data analysis. Given it's growth and success in industry, we utilize the MapReduce model to perform this analysis on a representative suite of scientific visualization tasks: isosurface extraction, mesh simplification, and rendering.

- Speaker: Jonathan Bronson (SCI), http://www.sci.utah.edu/people/bronson.html

- Where: Conference Room 3760

- When: Friday noon (03/12)

Mar. 5, 2010

- Fiedler Trees for Multiscale Surface Analysis

In this work we introduce a new hierarchical surface decomposition method for multiscale analysis of surface meshes. In contrast to other multiresolution methods, our approach relies on spectral properties of the surface to build a binary hierarchical decomposition. Namely, we utilize the Fiedler vector of the Laplace-Beltrami operator to recursively decompose the surface. For this reason, we coin our surface decomposition the Fiedler tree. Using the Fiedler tree ensures a number of attractive properties, including: mesh-independent decomposition, well-formed and equi-areal surface patches, and noise robustness. We illustrate how the hierarchical patch decomposition may be exploited for generating multiresolution high quality uniform and adaptive meshes, as well as being a natural means for carrying out wavelet methods.

- Speaker: Matt Berger (SCI), http://www.sci.utah.edu/people/bergerm.html

- Where: Conference Room 3760

- When: Friday noon (03/05)

Feb. 26, 2010

- Physically-Based Interactive Schlieren Flow Visualization (Pacific Vis 2010 Practice talk)

Understanding fluid flow is a difficult problemand of increasing importance as computational fluid dynamics produces an abundance of simulation data. Experimental flow analysis has employed techniques such as shadowgraph and schlieren imaging for centuries which allow empirical observation of inhomogeneous flows. Shadowgraphs provide an intuitive way of looking at small changes in flow dynamics through caustic effects while schlieren cutoffs introduce an intensity gradation for observing large scale directional changes in the flow. The combination of these shading effects provides an informative global analysis of overall fluid flow. Computational solutions for these methods have proven too complex until recently due to the fundamental physical interaction of light refracting through the flow field. In this paper, we introduce a novel method to simulate the refraction of light to generate synthetic shadowgraphs and schlieren images of time-varying scalar fields derived from computational fluid dynamics (CFD) data. Our method computes physically accurate schlieren and shadowgraph images at interactive rates by utilizing a combination of GPGPU programming, acceleration methods, and data-dependent probabilistic schlieren cutoffs. Results comparing this method to previous schlieren approximations are presented.

- Speaker: Carson Brownlee (SCI), http://www.sci.utah.edu/people/brownlee.html

- Where: Conference Room 3760

- When: Friday noon (02/26)

Feb. 19, 2010

- Visualizing Statistics for Uncertain Data, with Guarantees

We consider the problem of visualizing statistics on uncertain data. In particular, we assume we are given a data set where each data element has a probability distribution describing its uncertainty. This data arises in robotics, computational structural biology, biosurveillance, and many other important areas. Given a query statistic on this uncertain data, we argue that the answer to the query should itself be represented as a probability distribution. The talk will focus on creating and visualizing distributions for increasingly complicated types of queries: (a) univariate statistics, (b) multivariate statistics, and (c) shape inclusion probabilities (SIPs), which measure the probability that a query point is within a shape summarizing the data. The algorithms to create and visualize these structures are simple and practical; furthermore, we can prove guarantees on their accuracy. We will conclude with open problems, glimpses at ongoing work, and opportunities for collaboration.

(joint work w/ Maarten Loffler)

- Speaker: Jeff Phillips (CS), http://www.cs.utah.edu/~jeffp/

- Where: Conference Room 3760

- When: Friday noon (02/19)

Feb. 12, 2010

- Applying Manifold Learning to Plotting Approximate Contour Trees (VIS paper discussion)

- Speaker: Hao Wang (SCI), http://www.cs.utah.edu/~haow/

- Mapping Text with Phrase Nets (InfoVis paper discussion)

- Speaker: Claurissa Tuttle (SCI) http://www.sci.utah.edu/people/tuttle.html

- Where: Conference Room 3760

- When: Friday noon (02/12)

Feb. 5, 2010

-Distributed visualization using high-speed networks

I will talk about methods of designing a distributed visualization application to take advantage of high-speed networks and distributed resources to improve scalability, performance and capabilities. I will describe how, through distribution, a visualization application can be improved to interactively visualize tens of gigabytes of data and handle large datasets while maintaining high quality. The application supports interactive frame rates, high resolution, collaborative visualization and sustains remote I/O bandwidths of several Gbps.

I will also describe my research in remote data access systems motivated by the distributed visualization application. Because wide-area networks may have a high latency, the remote I/O system uses an architecture that effectively hides latency. Five remote data access architectures are briefly analyzed and the results show that an architecture that combines bulk and pipeline processing is the best solution for high-throughput remote data access. The resulting system, also supporting high-speed transport protocols and configurable remote operations, is up to 400 times faster than a comparable existing remote data access system.

Transport protocols are briefly compared to understand which protocol can best utilize high-speed network connections.

My talk will be concluded with a presentation of interesting future research areas, as well a presentation of the distributed visualization and cyberinfrastructure research project that was recently funded by the National Science Foundation and motivates my visit to Utah and interesting related collaboration areas.

- Speaker: Andrei Hutanu (Louisiana State University) http://www.cct.lsu.edu/~ahutanu/

- Where: Conference Room 3760

- When: Friday noon (02/05)